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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Filip Zorić Alejandro Suarez Goran Vasiljević Matko Orsag Zdenko Kovačić Anibal Ollero Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia GRVC Robotics Lab University of Seville Sevilla Spain

This paper presents a comparative performance evaluation of three different teleoperation interfaces for very low weight (<3 kg) anthropomorphic dual arms intended to conduct complex manipulation tasks involving a certain level of dexterity, accuracy and agility, either in ground service or in aerial manipulation applications. A visual human pose estimation system is developed to obtain the Cartesian and joint values of the user, which are mapped to the corresponding pose of the dual arm manipulator exploiting the equivalent human-robot kinematics. A leader-follower scheme is also presented, using a reduced scale dual arm that can replicate directly the joint positions of the leader arms to the follower arms. A 6-DOF (degrees of freedom) joystick is proposed to generate linear motions more accurately. A total of 60 ground tests were conducted involving 10 participants to determine the accuracy and time performance in two benchmarks (box edges and S contour tracking). Finally, the visual and leader-follower interfaces were evaluated with the dual arm aerial manipulator on flight tests, reporting several findings derived from the system evaluation.

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Feasibility Evaluation of Quadratic Programs for Constrained control

arXiv

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arXiv 2025年

作者： Rousseas, Panagiotis Panagou, Dimitra Control Systems Laboratory School of Mechanical Engineering National Technical University of Athens Greece Department of Robotics Department of Aerospace Engineering University of Michigan MI United States

This paper presents a computationally-efficient method for evaluating the feasibility of Quadratic Programs (QPs) for online constrained control. Based on the duality principle, we first show that the feasibility of a QP can be determined by the solution of a properly-defined Linear Program (LP). Our analysis yields a LP that can be solved more efficiently compared to the original QP problem, and more importantly, is simpler in form and can be solved more efficiently compared to existing methods that assess feasibility via LPs. The computational efficiency of the proposed method compared to existing methods for feasibility evaluation is demonstrated in comparative case studies as well as a feasible-constraint selection problem, indicating its promise for online feasibility evaluation of optimization-based controllers. © 2025, CC BY.

关键词： Quadratic programming

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Development of an Industrial Real-time Ethernet Protocol Stack Based on SoC

Development of an Industrial Real-time Ethernet Protocol Sta...

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2022 International Symposium on Networks, Computers and Communications, ISNCC 2022

作者： Zhang, Bo Yan, Bingjun Liu, Mingzhe Hu, Bo Xu, Aidong Wang, Kai Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

In order to improve the real-time and reliability of network communication in intelligent ship system, this paper analyzes the requirements of ship-borne network, and develops a real-time Ethernet protocol stack based on Zynq7000 series SoC chip. The development of the protocol stack includes the software layer and the firmware layer. As the main part of the protocol stack, the software layer adds real-time communication entities upon the data link layer of the Ethernet reference model, and the timing of communication is controlled by the synchronous precise measurement clock to realize the real-time scheduling and transmission of data. On the other hand, the PTP message timestamp function of clock synchronization and the redundant function of zero recovery time based on PRP algorithm is realized on the firmware layer. Finally, the real-time, reliability and synchronization accuracy of the protocol stack are tested and verified on the developed real-time Ethernet cards. © 2022 IEEE.

关键词： System-on-chip

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Kuhn-Munkres Algorithm Based Hybrid Beamforming for Wideband Millimeter Wave MIMO systems With Dynamic Subarrays 15

Kuhn-Munkres Algorithm Based Hybrid Beamforming for Wideband...

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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Wang, Gengshan Yang, Zhijia Gong, Tierui Zheng, Meng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Singapore University of Technology and Design Singapore

ISBN: (纸本)9798350324662

Dynamic subarrays (DSs) is an energy-efficient and cost-effective hybrid beamforming structure for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications. In this paper, we investigate the nonconvex hybrid beam-forming problem of maximizing the average spectral efficiency of the point-to-point wideband mmWave MIMO system with DSs, where the beam squints are also considered. To address the nonconvexity of this hybrid beamforming problem, we first exploit the singular value decomposition of each subcarrier channel and water-filling strategy to get the optimal fully-digital beamforming. We then propose to leverage the Kuhn-Munkres algorithm to get the hybrid beamforming from the obtained fully-digital solutions, aiming to guarantee that every radio-frequency chain is connected to at least one antenna. Besides, we analyze the computational complexity of the proposed design. Numerical results demonstrate the superiority of this work over the state of the art. © 2023 IEEE.

关键词： dynamic subarrays hybrid beamforming Kuhn-Munkres algorithm MIMO spectral efficiency Wideband millimeter wave

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Prior Knowledge Informed Neural Network for Subsurface Flow Prediction

Prior Knowledge Informed Neural Network for Subsurface Flow ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Haibo Cheng Shichao Li Peng Zeng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Data-driven deep learning has been widely applied to solve subsurface flow problems. However, it is difficult to achieve accurate prediction with pure data-driven methods, especially when there is only a small amount of valid data. Prior knowledge is pre-existent and comes from an independent source. The neural network can be informed by prior knowledge to improve algorithm performance even with limited and sparse data. In this study, prior knowledge informed neural network (PKINN) is proposed to predict subsurface flow. The prior knowledge, on the one hand, is embedded in the neural networks as integrated loss function to inform the training process of deep learning methods. On the other hand, it is used as part of input term of neural network to improve calculation accuracy. Subsurface flow models are built to verify the proposed PKINN model. The results show that the PKINN method can solve subsurface flow problems effectively.

关键词： Knowledge engineering Deep learning Training Industrial electronics Solid modeling Accuracy Neural networks

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A Portable and Integrated Traveling-Wave Electroosmosis Microfluidic Pumping System Driven by Triboelectric Nanogenerator

SSRN

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SSRN 2024年

作者： Zhou, Jian Tao, Ye Liu, Weiyu Sun, Tie Wu, Fangyu Shi, Changrui Ren, Yukun State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China School of Electronics and Control Engineering Chang'an University Xi’an710064 China

The lab-on-a-chip system can simultaneously complete the preparation, reaction, separation, and detection of samples on a centi-scale platform by manipulating trace fluids. Traveling-wave electroosmosis (TWEO) technology, with the merit of electric signal-based flexible control over the fluid behavior, can achieve precise driving of fluids, which is an important requirement of the lab-on-a-chip system. However, the peripheral power equipment such as function generator required for TWEO limits the application in some occasions lacking power supply facilities, due to its large size and high cost. In this paper, we developed a brand-new portable and integrated TWEO microfluidic pumping system, wherein a front-end module of triboelectric nanogenerator (TENG) is in serial connection with the back-end microfluidic pumping chip, which greatly improves portability and reduces costs. The TENG can output a stable four consecutively 90°-phase-shifted alternating current voltage signals in a continuous rotational motion originated by its novel electrode structure. And the four-phase traveling potential waves are applied to four sets of electrode strips alternately distributed in the microchannel and thereby induce nonlinear electroosmotic slip on the electrode surface. Compared with traditional mechanical pumps, this system achieves stable pumping of electrolyte in the microchannel, but also realizes the almost instantaneous start, stop, and directional switching in response to a turn on, turn off, and turn in reverse of TENG, respectively. Finally, this system is integrated into a droplet microfluidic chip for the efficient fabrication of single emulsion droplets. This study presents a promising solution for the miniaturization, integration, and commercialization of lab-on-a-chip system. © 2024, The Authors. All rights reserved.

关键词： Lab-on-a-chip

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Temperature Rising Model of Tubular Permanent Magnet Linear Synchronous Motor Based on Transfer Learning-Deep Neural Network

Temperature Rising Model of Tubular Permanent Magnet Linear ...

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第42届中国控制会议

作者： YiFei Wang Tao Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

High temperature rise of permanent magnet linear synchronous motor can lead to irreversible demagnetization of the motor permanent magnet, which can negatively affect the motor performance. To address this problem, a thermal modeling analysis method based on Transfer learning-Deep neural network(TL-DNN) was proposed in this paper. Its specific implementation steps include(1) corresponding to different heat source inputs, the equivalent thermal circuit method and the finite element analysis was adopted based on the structure and main parameters of PMLSM including overall average temperature rise, coil temperature rise and permanent magnet temperature rise from the data sets of the motor;(2) TL-DNN was used to fit the functional relationship between the input source features and the output targets based on the characteristics of the sample data sets. In order to verify the accuracy of the prediction model with small sample data sets, this paper divided the proportion of the data set and compared the results with other classic nonparametric models(random forest, support vector machine, and deep neural network). The results show that the TL-DNN model outperforms other machine learning models and has better robustness and generalization ability when the training datasets are insufficient, and achieves an organic combination of physical field path model and data-driven model, which provides a feasible solution for PMLSM modeling in the case of small samples.

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NA-CPG: A robust and stable rhythm generator for robot motion control

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Biomimetic Intelligence & robotics 2022年第4期2卷 30-38页

作者： Ru Tong Changlin Qiu Zhengxing Wu Jian Wang Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic ***,the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces,and the coupling of oscillators affects the network output accuracy in complex topological ***,CPGs may diverge when parameters change drastically,and the divergence is irreversible,which is catastrophic for the control of robot ***,normalized asymmetric CPGs(NA-CPGs)that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are ***-CPGs can realize parameter decoupling,precise amplitude output,and stable and rapid convergence,as well as asymmetric output ***,it can effectively cope with large parameter changes to avoid network oscillations and *** optimize the parameters of the NA-CPG model,a reinforcement-learning-based online optimization method is further ***,a biomimetic robotic fish is illustrated to realize the whole optimization *** demonstrated that the designed NA-CPGs exhibit stable,secure,and accurate network outputs,and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7%and 41.7%,*** proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.

关键词： Normalized asymmetric CPGs Rhythm generator Motion control Robotic fish

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A Weighting Factors Autotuning Strategy for Model Predictive Torque control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-objective Black Hole Algorithm

A Weighting Factors Autotuning Strategy for Model Predictive...

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第42届中国控制会议

作者： Zixiang Zhou Tao Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

The rational design of weighting factors in the cost function for finite control set model predictive torque control(FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor(PMSM) based on the adaptive multi-objective black hole algorithm(AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multiobjective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system.

关键词： Model Predictive Torque control Weighting Factors Multi-objective Optimization Algorithm Permanent Magnet Synchronous Motor

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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